


'''simple docstring'''


import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..utils.py_utils import no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
				from .features import FeatureType


UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_						:  Any				  =						False, False, False





@dataclass
class        lowercase__    :





							'''simple docstring'''


							A_				: Optional[int]       =    None
							A_				: bool       =    True
							A_				: bool       =    True
							A_				: Optional[str]       =    None
							# Automatically constructed
							A_				: ClassVar[str]       =    "dict"
							A_				: ClassVar[Any]       =    pa.struct({"""bytes""": pa.binary(), """path""": pa.string()}   )
							A_				: str       =    field(default="""Audio"""	,	init=_snake_case	,	repr=_snake_case   )






							def __call__(       self    ):
											return self.pa_type






							def UpperCAmelCase_      (       self       ,   __snake_case    ):
											try:
															import soundfile as sf  # soundfile is a dependency of librosa, needed to decode audio files.
											except ImportError as err:
															raise ImportError("""To support encoding audio data, please install 'soundfile'."""    ) from err
											if isinstance(__snake_case       ,   __snake_case    ):
															return {"bytes": None, "path": value}
											elif isinstance(__snake_case       ,   __snake_case    ):
															return {"bytes": value, "path": None}
											elif "array" in value:
															# convert the audio array to wav bytes
															_SCREAMING_SNAKE_CASE					:			str							= BytesIO()
															sf.write(__snake_case       ,   value["""array"""]       ,   value["""sampling_rate"""]       ,   format="""wav"""    )
															return {"bytes": buffer.getvalue(), "path": None}
											elif value.get("""path"""    ) is not None and os.path.isfile(value["""path"""]    ):
															# we set "bytes": None to not duplicate the data if they're already available locally
															if value["path"].endswith("""pcm"""    ):
																			# "PCM" only has raw audio bytes
																			if value.get("""sampling_rate"""    ) is None:
																							# At least, If you want to convert "PCM-byte" to "WAV-byte", you have to know sampling rate
																							raise KeyError("""To use PCM files, please specify a 'sampling_rate' in Audio object"""    )
																			if value.get("""bytes"""    ):
																							# If we already had PCM-byte, we don`t have to make "read file, make bytes" (just use it!)
																							_SCREAMING_SNAKE_CASE					:			List[Any]							= np.frombuffer(value["""bytes"""]       ,   dtype=np.intaa    ).astype(np.floataa    ) / 3_2767
																			else:
																							_SCREAMING_SNAKE_CASE					:			Tuple							= np.memmap(value["""path"""]       ,   dtype="""h"""       ,   mode="""r"""    ).astype(np.floataa    ) / 3_2767

																			_SCREAMING_SNAKE_CASE					:			Optional[Any]							= BytesIO(bytes()    )
																			sf.write(__snake_case       ,   __snake_case       ,   value["""sampling_rate"""]       ,   format="""wav"""    )
																			return {"bytes": buffer.getvalue(), "path": None}
															else:
																			return {"bytes": None, "path": value.get("""path"""    )}
											elif value.get("""bytes"""    ) is not None or value.get("""path"""    ) is not None:
															# store the audio bytes, and path is used to infer the audio format using the file extension
															return {"bytes": value.get("""bytes"""    ), "path": value.get("""path"""    )}
											else:
															raise ValueError(
															    f"""An audio sample should have one of 'path' or 'bytes' but they are missing or None in {value}."""    )






							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case = None    ):
											if not self.decode:
															raise RuntimeError("""Decoding is disabled for this feature. Please use Audio(decode=True) instead."""    )

											_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Any							= (value["""path"""], BytesIO(value["""bytes"""]    )) if value["""bytes"""] is not None else (value["""path"""], None)
											if path is None and file is None:
															raise ValueError(f"""An audio sample should have one of 'path' or 'bytes' but both are None in {value}."""    )

											try:
															import librosa
															import soundfile as sf
											except ImportError as err:
															raise ImportError("""To support decoding audio files, please install 'librosa' and 'soundfile'."""    ) from err

											_SCREAMING_SNAKE_CASE					:			Any							= xsplitext(__snake_case    )[1][1:].lower() if path is not None else None
											if not config.IS_OPUS_SUPPORTED and audio_format == "opus":
															raise RuntimeError(
															    """Decoding 'opus' files requires system library 'libsndfile'>=1.0.31, """
															    """You can try to update `soundfile` python library: `pip install \"soundfile>=0.12.1\"`. """    )
											elif not config.IS_MP3_SUPPORTED and audio_format == "mp3":
															raise RuntimeError(
															    """Decoding 'mp3' files requires system library 'libsndfile'>=1.1.0, """
															    """You can try to update `soundfile` python library: `pip install \"soundfile>=0.12.1\"`. """    )

											if file is None:
															_SCREAMING_SNAKE_CASE					:			List[Any]							= token_per_repo_id or {}
															_SCREAMING_SNAKE_CASE					:			List[Any]							= path.split("""::"""    )[-1]
															try:
																			_SCREAMING_SNAKE_CASE					:			str							= string_to_dict(__snake_case       ,   config.HUB_DATASETS_URL    )["""repo_id"""]
																			_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= token_per_repo_id[repo_id]
															except (ValueError, KeyError):
																			_SCREAMING_SNAKE_CASE					:			str							= None

															with xopen(__snake_case       ,   """rb"""       ,   use_auth_token=__snake_case    ) as f:
																			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Optional[Any]							= sf.read(__snake_case    )

											else:
															_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			List[str]							= sf.read(__snake_case    )

											_SCREAMING_SNAKE_CASE					:			List[str]							= array.T
											if self.mono:
															_SCREAMING_SNAKE_CASE					:			List[Any]							= librosa.to_mono(__snake_case    )
											if self.sampling_rate and self.sampling_rate != sampling_rate:
															_SCREAMING_SNAKE_CASE					:			Any							= librosa.resample(__snake_case       ,   orig_sr=__snake_case       ,   target_sr=self.sampling_rate    )
															_SCREAMING_SNAKE_CASE					:			List[str]							= self.sampling_rate

											return {"path": path, "array": array, "sampling_rate": sampling_rate}






							def UpperCAmelCase_      (       self    ):
											from .features import Value

											if self.decode:
															raise ValueError("""Cannot flatten a decoded Audio feature."""    )
											return {
											    "bytes": Value("""binary"""    ),
											    "path": Value("""string"""    ),
											}






							def UpperCAmelCase_      (       self       ,   __snake_case    ):
											if pa.types.is_string(storage.type    ):
															_SCREAMING_SNAKE_CASE					:			List[str]							= pa.array([None] * len(__snake_case    )       ,   type=pa.binary()    )
															_SCREAMING_SNAKE_CASE					:			Tuple							= pa.StructArray.from_arrays([bytes_array, storage]       ,   ["""bytes""", """path"""]       ,   mask=storage.is_null()    )
											elif pa.types.is_binary(storage.type    ):
															_SCREAMING_SNAKE_CASE					:			str							= pa.array([None] * len(__snake_case    )       ,   type=pa.string()    )
															_SCREAMING_SNAKE_CASE					:			Dict							= pa.StructArray.from_arrays([storage, path_array]       ,   ["""bytes""", """path"""]       ,   mask=storage.is_null()    )
											elif pa.types.is_struct(storage.type    ) and storage.type.get_all_field_indices("""array"""    ):
															_SCREAMING_SNAKE_CASE					:			Dict							= pa.array([Audio().encode_example(__snake_case    ) if x is not None else None for x in storage.to_pylist()]    )
											elif pa.types.is_struct(storage.type    ):
															if storage.type.get_field_index("""bytes"""    ) >= 0:
																			_SCREAMING_SNAKE_CASE					:			List[str]							= storage.field("""bytes"""    )
															else:
																			_SCREAMING_SNAKE_CASE					:			Dict							= pa.array([None] * len(__snake_case    )       ,   type=pa.binary()    )
															if storage.type.get_field_index("""path"""    ) >= 0:
																			_SCREAMING_SNAKE_CASE					:			Dict							= storage.field("""path"""    )
															else:
																			_SCREAMING_SNAKE_CASE					:			int							= pa.array([None] * len(__snake_case    )       ,   type=pa.string()    )
															_SCREAMING_SNAKE_CASE					:			Dict							= pa.StructArray.from_arrays([bytes_array, path_array]       ,   ["""bytes""", """path"""]       ,   mask=storage.is_null()    )
											return array_cast(__snake_case       ,   self.pa_type    )






							def UpperCAmelCase_      (       self       ,   __snake_case    ):

											@no_op_if_value_is_null
											def path_to_bytes(__snake_case    ):
															with xopen(__snake_case       ,   """rb"""    ) as f:
																			_SCREAMING_SNAKE_CASE					:			Optional[Any]							= f.read()
															return bytes_

											_SCREAMING_SNAKE_CASE					:			List[str]							= pa.array(
											    [
											        (path_to_bytes(x["""path"""]    ) if x["""bytes"""] is None else x["""bytes"""]) if x is not None else None
											        for x in storage.to_pylist()
											    ]       ,   type=pa.binary()       ,   )
											_SCREAMING_SNAKE_CASE					:			Tuple							= pa.array(
											    [os.path.basename(__snake_case    ) if path is not None else None for path in storage.field("""path"""    ).to_pylist()]       ,   type=pa.string()       ,   )
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= pa.StructArray.from_arrays([bytes_array, path_array]       ,   ["""bytes""", """path"""]       ,   mask=bytes_array.is_null()    )
											return array_cast(__snake_case       ,   self.pa_type    )








'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_						:  int				  =						{'configuration_wavlm': ['WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'WavLMConfig']}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  Tuple				  =						[
				    'WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'WavLMForAudioFrameClassification',
				    'WavLMForCTC',
				    'WavLMForSequenceClassification',
				    'WavLMForXVector',
				    'WavLMModel',
				    'WavLMPreTrainedModel',
				]

if TYPE_CHECKING:
				from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_wavlm import (
								    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
								    WavLMForAudioFrameClassification,
								    WavLMForCTC,
								    WavLMForSequenceClassification,
								    WavLMForXVector,
								    WavLMModel,
								    WavLMPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase_						:  Any				  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




